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Multiview learning has received substantial attention over the past decade due to its powerful capacity in integrating various types of information. Conventional unsupervised multiview dimension reduction (UMDR) methods are usually conducted in an offline manner and may fail in many real-world applications, where data arrive sequentially and the data distribution changes periodically. Moreover, satisfying the requirements of high memory consumption and expensive retraining of the time cost in large-scale scenarios are difficult. To remedy these drawbacks, we propose an online UMDR (OUMDR) framework. OUMDR aims to seek a low-dimensional and informative consensus representation for streaming multiview data. View-specific weights are also learned in this article to reflect the contributions of different views to the final consensus presentation. A specific model called OUMDR-E is developed by introducing the exclusive group LASSO (EG-LASSO) to explore the intraview and interview correlations. Then, we develop an efficient iterative algorithm with limited memory and time cost requirements for optimization, where the convergence of each update is theoretically guaranteed. We evaluate the proposed approach in video-based expression recognition applications. The experimental results demonstrate the superiority of our approach in terms of both effectiveness and efficiency.

It is an open question to give a combinatorial interpretation of the Falk invariant of a hyperplane arrangement, i.e. the third rank of successive quotients in the lower central series of the fundamental group of the arrangement. In this article, we give a combinatorial formula for this invariant in the case of hyperplane arrangements that are complete lift representation of certain gain graphs. As a corollary, we compute the Falk invariant for the cone of the braid, Shi, Linial and semiorder arrangements., Comment: To appear in Discrete & Computational Geometry. arXiv admin note: substantial text overlap with arXiv:1707.08449, arXiv:1703.09402

Iron is a trace metal that is found in animals, plants, and the human body. Human iron absorption is hampered by plant iron shortage, which leads to anemia. Leafy vegetables are one of the most direct and efficient sources of iron for humans. Despite the fact that ferrotrophic disorder is common in calcareous soil, however, non-heading Chinese cabbage performs a series of reactions in response to iron deficiency stress that help to preserve iron homeostasis in vivo. In this study, we discovered that iron deficiency stress caused leaf yellowing and impeded plant development in both iron-deficient and control treatments by viewing or measuring phenotypic, chlorophyll content, and Fe2+ content in both iron-deficient and control treatments. We found a total of 9213 differentially expressed genes (DEGs) in non-heading Chinese cabbage by comparing root and leaf transcriptome data with iron deficiency and control treatments. For instance, 1927 DEGs co-expressed in root and leaf, including 897 up-regulated and 1030 down-regulated genes, respectively. We selected some key antioxidant genes, hormone signal transduction, iron absorption and transport, chlorophyll metabolism, and transcription factors involved in the regulation of iron deficiency stress utilizing GO enrichment, KEGG enrichment, multiple types of functional annotation, and Weighted Gene Co-expression Network Analysis (WGCNA). This study identifies prospective genes for maintaining iron homeostasis under iron-deficient stress, offering a theoretical foundation for further research into the molecular mechanisms of greater adaptation to iron-deficient stress, and perhaps guiding the development of iron-tolerant varieties.

Human emotion recognition is an important issue in human–computer interactions, and electroencephalograph (EEG) has been widely applied to emotion recognition due to its high reliability. In recent years, methods based on deep learning technology have reached the state-of-the-art performance in EEG-based emotion recognition. However, there exist singularities in the parameter space of deep neural networks, which may dramatically slow down the training process. It is very worthy to investigate the specific influence of singularities when applying deep neural networks to EEG-based emotion recognition. In this paper, we mainly focus on this problem, and analyze the singular learning dynamics of deep multilayer perceptrons theoretically and numerically. The results can help us to design better algorithms to overcome the serious influence of singularities in deep neural networks for EEG-based emotion recognition.

Introduction High-fat diet (HFD)-induced obesity impairs clearance of cholesterol through the Reverse Cholesterol Transport (RCT) pathway, with downregulation in hepatic expression of cholesterol and bile acid transporters, namely ABCG5/8 and ABCB11, and reduced high-density lipoprotein (HDL) cholesterol efflux capacity (CEC). In the current study, we hypothesized that the development of hepatosteatosis, secondary to adipose-tissue dysfunction, contributes to obesity-impaired RCT and that such effects could be mitigated using the anti-inflammatory drug sodium salicylate (NaS). Materials and methods C57BL/6J mice, fed HFD ± NaS or low-fat diet (LFD) for 24 weeks, underwent glucose and insulin tolerance testing. The 3H-cholesterol movement from macrophage-to-feces was assessed in vivo. HDL-CEC was determined ex vivo. Cytokine secretion from adipose-derived stromal vascular fraction (SVF) cells was measured ex vivo. Liver and HDL proteins were determined by mass spectrometry and analyzed using Ingenuity Pathway Analysis. Results NaS delayed HFD-induced weight gain, abrogated priming of pro-IL-1β in SVFs, attenuated insulin resistance, and prevented steatohepatitis (ectopic fat accumulation in the liver). Prevention of hepatosteatosis coincided with increased expression of PPAR-alpha/beta-oxidation proteins with NaS and reduced expression of LXR/RXR-induced proteins including apolipoproteins. The latter effects were mirrored within the HDL proteome in circulation. Despite remarkable protection shown against steatosis, HFD-induced hypercholesterolemia and repression of the liver-to-bile cholesterol transporter, ABCG5/8, could not be rescued with NaS. Discussions and conclusions The cardiometabolic health benefits of NaS may be attributed to the reprogramming of hepatic metabolic pathways to increase fatty acid utilization in the settings of nutritional overabundance. Reduced hepatic cholesterol levels, coupled with reduced LXR/RXR-induced proteins, may underlie the lack of rescue of ABCG5/8 expression with NaS. This remarkable protection against HFD-induced hepatosteatosis did not translate to improvements in cholesterol homeostasis., Graphical abstract Image 1, Highlights • Sodium salicylate (NaS) initially delays weight-gain in mice fed high-fat diet (HFD) - catch-up evident in weeks 12–24. • NaS prevents HFD-induced insulin resistance, hepatosteatosis and pro-IL-1β priming in adipose tissue even upon weight-gain. • Hepatic expression of proteins involved in beta oxidation, oxidative phosphorylation and TCA cycle upregulated with NaS. • Hepatic expression of LXR/RXR proteins eg. apolipoproteins reduced with NaS; these effects were mirrored in HDL proteome. • NaS failed to improve HFD-impaired Reverse Cholesterol Transport or hypercholesterolemia despite preventing hepatosteatosis.

The number and proportion of female flowers per plant can directly influence the yield and economic benefits of cucurbit crops. Ethephon is often used to induce female flowers in cucurbits. However, the mechanism through which it affects floral sex differentiation in pumpkin is unknown. We found that the application of ethephon on shoot apical meristem of pumpkin at seedling stage significantly increased the number of female flowers and expedited the appearance of the first female flower. These effects were further investigated by transcriptome and hormone analyses of plants sprayed with ethephon. A total of 647 differentially expressed genes (DEGs) were identified, among which 522 were upregulated and 125 were downregulated. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis indicated that these genes were mainly enriched in plant hormone signal transduction and 1-aminocyclopropane-1-carboxylate oxidase (ACO). The results suggests that ethylene is a trigger for multiple hormone signaling, with approximately 4.2% of the identified DEGs involved in ethylene synthesis and multiple hormone signaling. Moreover, ethephon significantly reduced the levels of jasmonic acid (JA), jasmonoyl-L-isoleucine (JA-ILE), and para-topolin riboside (pTR) but increased the levels of 3-indoleacetamide (IAM). Although the level of 1-aminocyclopropanecarboxylic acid was not changed, the expression of ACO genes, which code for the enzyme catalyzing the key rate-limiting step in ethylene production, was significantly upregulated after ethephon treatment. The results indicate that the ethephon affects the transcription of ethylene synthesis and signaling genes, and other hormone signaling genes, especially auxin responsive genes, and modulates the levels of auxin, jasmonic acid, and cytokinin (CK), which may together contribute to femaleness.

Cadmium (Cd) as a carcinogen poses a great threat to food security and public health through plant-derived foods such as rice, the staple for nearly half of the world's population. We have previously reported that overexpression of truncated gene fragments derived from the rice genes OsO3L2 and OsO3L3 could reduce Cd accumulation in transgenic rice. However, we did not test the full length genes due to prior work in Arabidopsis where overexpression of these genes caused seedling lethality. Here, we report on limiting the overexpression of OsO3L2 and OsO3L3 through the use of the stress- inducible promoter RD29B. However, despite generating 625 putative transformants, only 7 lines survived as T1 seedlings and only 1 line of each overexpressed OsO3L2 or OsO3L3-produced T2 progeny. The T2 homozygotes from these 2 lines showed the same effect of reducing accumulation of Cd in root and shoot as well as in T3 grain. As importantly, the concentrations of essential metals copper (Cu), iron (Fe), manganese (Mn) and zinc (Zn) were unaffected. Analysis of the expression profile suggested that low Cd accumulation may be due to high expression of OsO3L2 and OsO3L3 in the root tip region. Cellular localization of OsO3L2 and OsO3L3 indicate that they are histone H2A interacting nuclear proteins in vascular cells and especially in the root tip region. It is possible that interaction with histone H2A modifies chromatin to regulate downstream gene expression.

Press-pack IGBTs are now widely used in HVDC and FACTS since its extraordinary reliability and high power density. A method to estimate the reliability of press-pack IGBT based on FEM is proposed. A circuit model of MMC was simulated by Simplorer in order to obtain the power loss model of press-pack IGBT. The coupled steady-state simulation of thermal, electrical and mechanical model was analyzed by Workbench. Furthermore, the transient junction swing of IGBT was estimated by a power loss with half sine profile. LESIT lifetime prediction model was used to analyze the lifetime and reliability of press-pack IGBT in MMC system. Press-pack IGBT has high reliability in MMC in long time scale since the low junction temperature of it.

For the widely used multilayer perceptrons (MLPs), the existed singularities in the parameter space have seriously affected the learning dynamics of MLPs, which cause several singular learning behaviors. Since the Fisher information matrix (FIM) plays a significant role in analyzing the singular learning dyanmics of MLPs, it is very worthy to obtain the analytical form of FIM to do further investigation. In this paper, by choosing the bipolar error function as the activation function, the analytical form of FIM are obtained, where the validity of the obtained results are verified by taking three experiments.

The prevalence of atherosclerosis is increased in type 1 diabetes despite normal-to-high HDL-cholesterol levels. The cholesterol efflux capacity (CEC) of HDL is a better predictor of cardiovascular events than static HDL-cholesterol. This cross-sectional study addressed the hypothesis that impaired HDL function contributes to enhanced CVD risk within type 1 diabetes. We compared HDL particle size and concentration (by NMR), total CEC, ATP-binding cassette subfamily A, member 1 (ABCA1)-dependent CEC and ABCA1-independent CEC (by determining [3H]cholesterol efflux from J774-macrophages to ApoB-depleted serum), and carotid intima–media thickness (CIMT) in 100 individuals with type 1 diabetes (37.6 ± 1.2 years; BMI 26.9 ± 0.5 kg/m2) and 100 non-diabetic participants (37.7 ± 1.1 years; 27.1 ± 0.5 kg/m2). Compared with non-diabetic participants, total HDL particle concentration was lower (mean ± SD 31.01 ± 8.66 vs 34.33 ± 8.04 μmol/l [mean difference (MD) −3.32 μmol/l]) in participants with type 1 diabetes. However, large HDL particle concentration was greater (9.36 ± 3.98 vs 6.99 ± 4.05 μmol/l [MD +2.37 μmol/l]), resulting in increased mean HDL particle size (9.82 ± 0.57 vs 9.44 ± 0.56 nm [MD +0.38 nm]) (p

and purpose: Massage therapy is being used for knee osteoarthritis. However, level-1 evidence is lacking. This systematic review and meta-analysis aimed to synthesize evidence on the effect of massage therapy on knee osteoarthritis.PubMed, Embase, Ovid, Springer, and Google Scholar databases were searched up to May 8, 2021 for randomized controlled trials comparing massage with controls for knee osteoarthritis. Review manager was used for a random-effect meta-analysis. Risk of bias was assessed using the Cochrane collaboration risk assessment tool and certainty of evidence using Grading of Recommendations Assessment, Development, and Evaluation (GRADE).Twelve studies with 737 participants were included. After 1-4 weeks of therapy, there was a significant reduction in pain and stiffness scores in the massage group and after 6-8 weeks of therapy, there was a significant reduction in stiffness and functionality scores. There was no significant difference in outcomes with long-term therapy. A statistically significant reduction in stiffness scores was seen with aromatherapy massage. Aromatherapy massage was not superior to standard massage. The overall quality of evidence according to GRADE was low to moderate for standard massage therapy and very low for aromatherapy.Massage therapy may lead to some improvement in pain, stiffness, and functionality scores in the short term but not in long term. Aromatherapy massage was not found to be any better than standard massage therapy. Current evidence is limited by methodological heterogeneity amongst trials and small sample size of the studies.

The fundamental group of the complement of a hyperplane arrangement in a complex vector space is an important topological invariant. The third rank of successive quotients in the lower central series of the fundamental group was called Falk invariant of the arrangement since Falk gave the first combinatorial formula and asked to give a combinatorial interpretation. In this article we prove that the Falk invariant of an arrangement associated with signed graph G without loops is double of the sum of $$k_3$$ , $$k_4$$ and $$k^{\pm }_3,$$ where $$k_l$$ is the number of subgraphs of G that are switching equivalent to the cliques with l vertices, $$k_3^{\pm }$$ is that of subgraphs which have 3 vertices and each two vertices are connected by double edges with different signs. This formula modifies the one given by Schenck and Suciu, and answers partially Falk’s question in the case of signed graphic arrangements.

For the bipolar-activation-function multilayer perceptrons (MLPs), there exist opposite singularities in the parameter space. The Fisher information matrix degenerates on the opposite singularity which causes strange learning behaviors. As the stability is the fundamental to analyze the properties of the opposite singularity, this paper concerns the stability analysis of the opposite singularity in MLPs. The analytical form of the best approximation on the opposite singularity is obtained at first, then the concrete expression of Hessian matrix can be obtained. By analyzing the eigenvalues of Hessian matrix on the opposite singularity, the stability of the opposite singularity is investigated. Finally, two experiments are taken to verify the obtained results.

The existing overlap singularities in the parameter space significantly affect the learning dynamics of the multilayer perceptrons. From the obtained theoretical learning trajectories near overlap singularity, when the learning process has been affected by the overlap singularity, the influence area of the overlap singularity is just the line space where the two hidden units equal to each other. However, in the practical applications, different case has been observed and the influence area of such singularity may be larger. By analyzing the generalization error of multilayer perceptrons, we find that the error surface is much flatter near overlap singularity and the singularity would have much larger influence area. Finally, the validity of the obtained results are verified by taking an artificial experiment and two real-data experiments.

The fundamental group of the complement of a hyperplane arrangement in a complex vector space is an interesting and complicated invariant. The third rank of successive quotients in the lower central series of the fundamental group was called the global invariant of the arrangement by Falk. Falk gave a general formula to compute the global invariant, and asked for a combinatorial interpretation of the global invariant. Schenck and Suciu proved that the global invariant of a graphic arrangement is double of the number of cliques with three or four vertices in the graph with which the arrangement associated. This solved Falk’s problem in the case of graphic arrangements. While in the case of signed graphic arrangements, we obtained a similar combinatorial formula. In this paper, we give a direct and simple proof for this combinatorial formula.

Background Exposure to fine particulate matter (PM2.5) has been associated with respiratory morbidity and mortality. Identification of interventional measures that are efficacious against PM2.5-induced toxicity may provide public health benefits. This study examined the inhibitory effects of nutritional supplementation with fish oil as a source of omega-3 fatty acids and vitamin E (Vit E) on PM2.5-induced lung toxicity in rats. Method Sixty four male Sprague Dawley rats were gavaged with phosphate buffered saline (PBS), corn oil (5 ml/kg), fish oil (150 mg/kg), or Vit E (75 mg/kg), respectively, once a day for 21 consecutive days prior to intratracheal instillation of PM2.5 (10 mg/kg) every other day for a total of 3 times. Serum and bronchoalveolar lavage fluids (BALFs) were collected 24 h after the last instillation of PM2.5. Levels of total proteins (TP), lactate dehydrogenase (LDH), superoxide dismutase (SOD), 8-epi-prostaglandin F2α (8-epi-PGF2α), interleukin-1β (IL-1β), C-reactive protein (CRP), IL-6, and tumor necrosis factor-ɑ (TNF-ɑ) were analyzed for markers of cell injury and inflammation. Additionally, histological alterations of lung tissues were examined by hematoxylin-eosin staining. Result Exposure to PM2.5 resulted in lung toxicity, represented as increased levels of total proteins, LDH, 8-epi-PGF2α, IL-1β and TNF-α, and increased infiltration of inflammatory cells, and decreased SOD in the BALFs, and systemic inflammation, as evinced by increased levels of CRP and IL-6 in serum. Strikingly, supplementation with fish oil but not Vit E significantly ameliorated PM2.5-induced lung toxicity and systemic inflammation. Conclusion PM2.5 exposure induces oxidative stress, lung injury and inflammation, which is ameliorated significantly by fish oil and partially by Vit E.

Background— Acute inflammation impairs reverse cholesterol transport (RCT) and reduces high-density lipoprotein (HDL) function in vivo. This study hypothesized that obesity-induced inflammation impedes RCT and alters HDL composition, and investigated if dietary replacement of saturated (SFA) for monounsaturated (MUFA) fatty acids modulates RCT. Methods and Results— Macrophage-to-feces RCT, HDL efflux capacity, and HDL proteomic profiling was determined in C57BL/6j mice following 24 weeks on SFA- or MUFA-enriched high-fat diets (HFDs) or low-fat diet. The impact of dietary SFA consumption and insulin resistance on HDL efflux function was also assessed in humans. Both HFDs increased plasma 3 H-cholesterol counts during RCT in vivo and ATP-binding cassette, subfamily A, member 1–independent efflux to plasma ex vivo, effects that were attributable to elevated HDL cholesterol. By contrast, ATP-binding cassette, subfamily A, member 1–dependent efflux was reduced after both HFDs, an effect that was also observed with insulin resistance and high SFA consumption in humans. SFA-HFD impaired liver-to-feces RCT, increased hepatic inflammation, and reduced ABC subfamily G member 5/8 and ABC subfamily B member 11 transporter expression in comparison with low-fat diet, whereas liver-to-feces RCT was preserved after MUFA-HFD. HDL particles were enriched with acute-phase proteins (serum amyloid A, haptoglobin, and hemopexin) and depleted of paraoxonase-1 after SFA-HFD in comparison with MUFA-HFD. Conclusions— Ex vivo efflux assays validated increased macrophage-to-plasma RCT in vivo after both HFDs but failed to capture differential modulation of hepatic cholesterol trafficking. By contrast, proteomics revealed the association of hepatic-derived inflammatory proteins on HDL after SFA-HFD in comparison with MUFA-HFD, which reflected differential hepatic cholesterol trafficking between groups. Acute-phase protein levels on HDL may serve as novel biomarkers of impaired liver-to-feces RCT in vivo.

Cadmium (Cd) is a toxic heavy metal and carcinogen, and its entry into the food chain has serious effects on food security and public health (Uraguchi et al., 2011). As rice is a staple food crop for half of the world’s population, Cd in rice grain has become a major source of dietary Cd for this part of the world. Previous gene discovery efforts for the development of low Cd rice have been linked to cation transport; and for the two most effective genes, OsHMA3 and OsNRAMP5, expression in yeast can cause a Cd-sensitive phenotype (Ueno et al., 2010; Ishikawa et al., 2012).

Obesity is associated with increased risk of cardiovascular disease (CVD) due to imbalances in lipid metabolism and leads to maladaptive inflammatory responses. This study assessed the effects of an obesogenic diet supplemented with anti-inflammatory sodium salicylate (NaS) on hepatic health, HDL proteomic quality, HDL functionality and Reverse Cholesterol Transport (RCT). RCT was assessed after 24 weeks in C57BL/6 mice fed a high fat (HFD) (60% fat) ± NaS (6g/kg) diet or low-fat diet (LFD, 10% fat) by tracing 3 H-cholesterol movement from labelled macrophages, injected intraperitoneally, into plasma, liver and fecal compartments. HDL particles were separated from plasma by fast protein liquid chromatography (FPLC) and associated proteins were identified by mass spectrometry. HDL particles were incubated with 3 H-cholesterol-labelled macrophages ex vivo and cholesterol efflux to HDL particles was determined by liquid scintillation counting (LSC). Both HFDs significantly increased HDL cholesterol mass. Nonetheless, HFD alone impaired hepatic movement of 3 H-cholesterol to fecal compartments coincident with increased hepatic lipid infiltration and inflammation. NaS supplementation increased all steps of macrophage-to-feces RCT with partial preservation of hepatic transporters while impeding hepatic lipid load and reducing markers of inflammation (ALT & AST). HFD resulted in enrichment of HDL particles with coagulant proteins (fibrinogen, coagulation factor IX) and a dissociation of anti-thrombin and angiotensinogen compared to HFD+NaS. NaS supplementation also preserved ABCA1-mediated efflux capacity of HDL particles. Obesogenic diets augmented with NaS resulted in profound differences within the RCT pathway and HDL proteome. HFD supplemented with NaS was associated with improved hepatic condition and HDL proteomic profile with an increase of anticoagulant and anti-atherogenic proteins on HDL despite development of obesity.

The multilayer perceptrons (MLPs) are widely used in many fields, however, singularities in the parameter space may seriously influence the learning dynamics of MLPs and cause strange learning behaviors. Given that the singularities are the subspaces of the parameter space where the Fisher information matrix (FIM) degenerates, the FIM plays a key role in the study of the singular learning dynamics of the MLPs. In this paper, we obtain the analytical form of the FIM for unipolar activation function-based MLPs where the input subjects to the Gaussian distribution with general covariance matrix and the unipolar error function is chosen as the activation function. Then three simulation experiments are taken to verify the validity of the obtained results.

The multilayer perceptron is one of the most widely used neural networks in applications, however, its learning behavior often becomes very slow, which is due to the singularities in the parameter space. In this paper, we analyze the learning dynamics near singularities in multilayer perceptrons by using traditional methods. We obtain the explicit expressions of the averaged learning equations which play a significant role in theoretical and numerical analysis. After obtaining the best approximation on overlap singularity, the stability of overlap singularity is analyzed. Then we take the numerical analysis on singular regions. Real averaged dynamics near the singularities are obtained in comparison with the theoretical learning trajectories near singularity. In the simulation we analyze the averaged learning dynamics, batch mode learning dynamics and on-line learning dynamics, respectively.

The multilayer perceptrons (MLPs) have been widely used in many communication applications, however, the learning process of the multilayer perceptrons often becomes very slow, which is due to the existence of the singularities in the parameter space. As the singularities significantly affect the learning dynamics of MLPs, the standard gradient descent method is not Fisher efficient. In order to overcome this problem, natural gradient method and adaptive natural gradient method were proposed to accelerate the learning process. As is well known, step size in each iteration plays a key role in the performance of algorithms. In this paper, the modified adaptive natural gradient method is proposed where the step size in each iteration is adaptive modified. The aim of the proposed algorithm is to accelerate the convergence speed and increase the performance of MLPs. The simulation results verify the validity of the analytical results.

The fundamental group of the complement of a hyperplane arrangement in a complex vector space is an important topological invariant. The third rank of successive quotients in the lower central series of the fundamental group was called Falk invariant of the arrangement since Falk gave the first formula and asked to give a combinatorial interpretation. In this article, we give a combinatorial formula for the Falk invariant of hyperplane arrangements attached to certain gain graphs., To appear in the Australasian Journal of Combinatorics. arXiv admin note: text overlap with arXiv:1703.09402

The fundamental group of the complement of a hyperplane arrangement in a complex vector space is an important topological invariant. The third rank of successive quotients in the lower central series of the fundamental group was called Falk invariant of the arrangement since Falk gave the first formula and asked to give a combinatorial interpretation. In this article, we give a combinatorial formula for the Falk invariant of a signed graphic arrangement that do not have a $$B_2$$ as sub-arrangement.

As is well known, the parameter spaces of hierarchical systems such as multilayer perceptrons include singularities and the plateau phenomenon is ubiquitous in the process of learning. In the singular regions, the Fisher information matrix degenerates and the loss function is almost unchanged when the parameters arrive in the singular regions, which is called the plateau phenomenon. We wonder about whether the singularities and the plateau phenomenon exist in the parameter identification process of the linear and the ordinary nonlinear systems. In this paper, we can see that in some of the parameter identification of the nonlinear systems, the Fisher information matrix degenerates, the singularities exist and we can see the plateau phenomenon in the learning curves. A simulation example is provided to demonstrate the theoretical analysis in Section 3 .

The multilayer perceptrons (MLPs) have strange behaviors in the learning process caused by the existing singularities in the parameter space. A detailed theoretical or numerical analysis of the MLPs is difficult due to the non-integrability of the traditional log-sigmoid activation function which leads to difficulties in obtaining the averaged learning equations (ALEs). In this paper, the error function is suggested as the activation function of the MLPs. By solving the explicit expressions of two important expectations, we obtain the averaged learning equations which make it possible for further analysis of the learning dynamics in MLPs. The simulation results also indicate that the ALEs play a significant role in investigating the singular behaviors of MLPs.

Feature selection is a significant preprocessing procedure for many high-dimensional forecasting problems. In multivariate time series forecasting, the purpose of feature selection is to select a relevant feature subset from the original time series. One of the most common strategies for feature selection is mutual information (MI) criterion. K-nearest neighbors (k-NN) is a powerful means which has been widely used to estimate the MI between two high-dimensional variables directly from data set. In order to improve the effect of feature selection, a novel procedure is proposed in this paper to use MI and k-NN to perform feature selection in multivariate time series forecasting. This feature selection procedure not only reduces the irrelevance between the inputs and outputs variables, but also removes the redundant input variables. The procedure of this method is elaborated on a synthetic data set as well as on a real-world example.

To avoid unpredictable losses because of network failure, the reliability of the network needs to be evaluated in some application scenarios. This paper start the network failure prediction research upon 14 months' network alarm logs we collected. The logs are of one Metropolitan area network. The research method is shown as below: firstly, construct features to represent network characteristics by the means of the feature construction method which is based on two levels time windows; secondly, select optimal parameter combination to create the feature files through multiple experiments; thirdly, design and build adaptive failure prediction model according to classification learning methods. Numbers of experiments show that accuracy of predicting whether the network failure takes place in 6 hours is up to 70%, is better than the prediction result of Weibull distribution model obviously; the results of classification prediction for network equipment failure are slightly better than the prediction method on the basis of Weibull distribution. Preliminary research results show that most network failures can be predicted through analyzing previous network running logs and the method proposed in this paper is verified to be with good prediction effect. This method can detect failures in practical application on early stage and reduce unnecessary economic losses.

Based on analyzing the multi-scale segmentation technique of watershed transform, by combining the multiple features of textured images, spectra and shape, an integrated image segmentation method of a combination of watershed and multi-scale can be presented. This article is combined with object-oriented technology, and applied it to extracting the information of arable land in Guangxi. The paper aims to establish classification system to solve the problem of extracting feature information by extracting the feature or feature combination of the class. The experimental result showed that the object-oriented extraction method of arable land information based on a combination of watershed and multi-scale could be better to realize extract and apply the information of high resolution remote sensing image.

We introduce a system of ferroelectric materials, Pb0.3CaxSr0.7-xTiO3 [PCST(x), x = 0.00, 0.05, 0.10, and 0.15], which exhibit good pyroelectric properties near room temperature. The enhanced field-induced pyroelectric coefficient of PCST(0.15) reached 81.8 × 10−8 C/cm2 K and it exhibited the largest voltage response with a dynamic black-body radiation measurement under a DC bias field of 200 V/mm. Systematic dielectric and phase transition analysis of the PCST(x) ceramics demonstrated that the phase transition gradually changed from a second-order to first-order dominated one with increasing Ca ion substitution. The enhanced pyroelectric properties under such a low bias field in the vicinity of room temperature of the PCST(0.15) ceramic are highly desirable for infrared detecting applications.

Radial basis function (RBF) networks are one of the most widely used models for function approximation and classification. There are many strange behaviors in the learning process of RBF networks, such as slow learning speed and the existence of the plateaus. The natural gradient learning method can overcome these disadvantages effectively. It can accelerate the dynamics of learning and avoid plateaus. In this letter, we assume that the probability density function (pdf) of the input and the activation function are gaussian. First, we introduce natural gradient learning to the RBF networks and give the explicit forms of the Fisher information matrix and its inverse. Second, since it is difficult to calculate the Fisher information matrix and its inverse when the numbers of the hidden units and the dimensions of the input are large, we introduce the adaptive method to the natural gradient learning algorithms. Finally, we give an explicit form of the adaptive natural gradient learning algorithm and compare it to the conventional gradient descent method. Simulations show that the proposed adaptive natural gradient method, which can avoid the plateaus effectively, has a good performance when RBF networks are used for nonlinear functions approximation.

This paper proposes a hybrid damping design to control torsional vibration of a shaft with a circular cross section through use of actively constrained layer (ACL) damping treatments proposed by Baz (1993) and Shen (1993, 1994a). The ACL damping treatment consists of a piezoelectric constraining layer and a viscoelastic shear layer wrapping around the shaft in the form of a helix. In addition, the angular displacement of the shaft is fed back to regulate the helical motion of the piezoelectric constraining layer. The equation of motion of this design is derived, and its stability and controllability are discussed. Finally, numerical examples show that this ACL design can reduce torsional vibration of a shaft. A sensitivity analysis shows that ACL is most effective in suppressing those modes with significant torsional vibration response. Stability, in general, is not a critical factor in designing ACL systems, because the piezoelectric strain of the constraining layer at the threshold of instability is too large to occur.

BackgroundtRNase Z removes the 3'-trailer sequences from precursor tRNAs, which is an essential step preceding the addition of the CCA sequence. tRNase Z exists in the short (tRNase ZS) and long (tRNase ZL) forms. Based on the sequence characteristics, they can be divided into two major types: bacterial-type tRNase ZSand eukaryotic-type tRNase ZL, and one minor type,Thermotoga maritima(TM)-type tRNase ZS. The number of tRNase Zs is highly variable, with the largest number being identified experimentally in the flowering plantArabidopsis thaliana. It is unknown whether multiple tRNase Zs found inA. thalianais common to the plant kingdom. Also unknown is the extent of sequence and structural conservation among tRNase Zs from the plant kingdom.ResultsWe report the identification and analysis of candidate tRNase Zs in 27 fully sequenced genomes of green plants, the great majority of which are flowering plants. It appears that green plants contain multiple distinct tRNase Zs predicted to reside in different subcellular compartments. Furthermore, while the bacterial-type tRNase ZSs are present only in basal land plants and green algae, the TM-type tRNase ZSs are widespread in green plants. The protein sequences of the TM-type tRNase ZSs identified in green plants are similar to those of the bacterial-type tRNase ZSs but have distinct features, including the TM-type flexible arm, the variant catalytic HEAT and HST motifs, and a lack of the PxKxRN motif involved in CCA anti-determination (inhibition of tRNase Z activity by CCA), which prevents tRNase Z cleavage of mature tRNAs. Examination of flowering plant chloroplast tRNA genes reveals that many of these genes encode partial CCA sequences. Based on our results and previous studies, we predict that the plant TM-type tRNase ZSs may not recognize the CCA sequence as an anti-determinant.ConclusionsOur findings substantially expand the current repertoire of the TM-type tRNase ZSs and hint at the possibility that these proteins may have been selected for their ability to process chloroplast pre-tRNAs with whole or partial CCA sequences. Our results also support the coevolution of tRNase Zs and tRNA 3'-trailer sequences in plants.

A 20-m drop tube was used to study the solidification of Pd43.5Ni43.5P13 alloy in free fall. The solidified droplets were identified by x-ray diffraction, scanning electron microscopy and x-ray energy dispersive spectrum analysis. The results showed that a near single phase of Pd-Ni-P fcc solid solution was obtained.